The invention relates to an intelligent technique for learning user interests based on user actions and then applying the learned knowledge to rank, recommend, and/or filter new items based on the level of interest to a user. More particularly the invention relates to an automated, personalized information learning and recommendation engine for a multitude of offerings, such as television programming, web-based auctions, targeted advertising, and electronic mail filtering. The embodiment is structured to generate item descriptions, learn items of interest, learn terms that effectively describe the items, cluster similar items in a compact data structure, and then use the structure to rank new offerings.